Figure 1
Abstract
Creating a trailer requires carefully picking out and piecing together brief enticing moments out of a longer video, making it a challenging and time-consuming task. This requires selecting moments based on both visual and dialogue information. We introduce a multi-modal method for predicting the trailerness to assist editors in selecting trailer-worthy moments from long-form videos. We present results on a newly introduced soap opera dataset, demonstrating that predicting trailerness is a challenging task that benefits from multi-modal information.
Type
Publication
In MultiMedia Modeling
Carlo Bretti
PhD candidate
My research lays at the intersection of computer vision and film, with applications on automatic trailer generation and retrieval.